Telecommunications network planning system

ABSTRACT

Systems and methods to identify a growth classification/categorization for a geographic area that helps a network provider to solve for what types of planning opportunities are available at various area granularities is disclosed. The system computes values for a set of growth criteria for a geographic area. The growth criteria are related to planning, usability, customer experience, sales, population, and so on. Based on the growth-criteria values, the system identifies a classification/categorization for the area. For example, the system classifies an area as an invest area (e.g., requiring engineering action), a grow area (e.g., requiring sales action/being sales ready), a defend area (e.g., requiring engineering and sales actions to continue current trend), or a fix area (e.g., likely requiring both engineering and sales actions to improve current trend). Based on the area classification, the system can then provide actionable insights to drive improvement in network coverage and customer experience.

CROSS REFERENCE TO RELATED APPLICATION(S)

This application is related to U.S. application Ser. No. 17/554,595,filed on Dec. 17, 2021, the contents of which are incorporated byreference in their entirety.

BACKGROUND

A telecommunications network is established via a complex arrangementand configuration of many cell sites that are deployed across ageographic area. For example, there can be different types of cell sites(e.g., macro cells, micro cells, and so on) positioned in a specificgeographical location, such as a city, a neighborhood, and so on. Thesecell sites strive to provide adequate, reliable coverage for mobiledevices (e.g., smart phones, tablets, and so on) via different frequencybands and radio networks such as a Global System for Mobile (GSM) mobilecommunications network, a code/time division multiple access (CDMA/TDMA)mobile communications network, a third or fourth generation (3G/4G)mobile communications network (e.g., General Packet Radio Service(GPRS), Enhanced GPRS (EGPRS)), Enhanced Data rates for GSM Evolution(EDGE), a Universal Mobile Telecommunications System (UMTS) or Long-TermEvolution (LTE) network, a 5G mobile communications network, Instituteof Electrical and Electronics Engineers (IEEE) 802.11 (Wi-Fi), or othercommunications network. The devices can seek access to thetelecommunications network for various services provided by the network,such as services that facilitate the transmission of data over thenetwork and/or provide content to the devices.

As device usage continues to rise at an impressive rate, there are toomany people using too many network- and/or data-hungry applications inplaces where the wireless edge of the telecommunications network haslimited or no capacity. As a result, most telecommunications networkshave to contend with issues of network congestion. Network congestion isthe reduced quality of service that occurs when a network node carriesmore data than it can handle. Typical effects include queueing delay,packet loss, and the blocking of new connections, resulting in anoverall degraded customer experience. As a result, a customer'sexperience with a network suffers and often results in a customerswitching telecommunications service providers.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram that illustrates a wireless telecommunicationsystem.

FIG. 2 is a block diagram that illustrates 5G core network functions(NFs) that can implement aspects of the present technology.

FIG. 3 is a block diagram that illustrates components of a networkplanning system.

FIG. 4 is a flow diagram that illustrates a process of optimizingcoverage in a telecommunications network.

FIG. 5 is an example diagram that illustrates processes (or componentsof processes) of optimizing coverage in a telecommunications network.

FIG. 6 illustrates some example geographic area classifications.

FIG. 7 is an example report that illustrates the impact of deployingvarious performance improvement solutions/actions on the classificationsfor various geographic areas in a region.

FIGS. 8A-8D are example reports that illustrate analysis of datarelating to network planning in a telecommunications network.

FIG. 9 is a block diagram that illustrates an example of a computersystem in which at least some operations described herein can beimplemented.

In the drawings, some components and/or operations can be separated intodifferent blocks or combined into a single block for discussion of someof the implementations of the present technology. Moreover, while thetechnology is amenable to various modifications and alternative forms,specific implementations have been shown by way of example in thedrawings and are described in detail below. The intention, however, isnot to limit the technology to the specific implementations described.On the contrary, the technology is intended to cover all modifications,equivalents, and alternatives falling within the scope of the technologyas defined by the appended claims.

DETAILED DESCRIPTION

Telecommunications network providers typically spend considerableresources (e.g., engineering resources, sales resources, etc.) invarious geographic areas to improve customer experience and grow theirnetwork. However, it is difficult for network providers to determinewhat types of network planning/improvement solutions to employ in anarea. For instance, while engineering solutions (e.g., adding a new cellsite, adding a new sector, deploying a small cell, etc.) may be suitedfor one area, sales solutions (e.g., offering discounts, increasingmarketing campaign spend, etc.) may be better suited for another area.As another example, after a network provider has deployed engineeringsolutions in an area to prepare it for handling new/increased customerload, the next step may be to deploy sales solutions to make customersaware of the improvements. Current systems do not provide actionableinsights regarding the types of targeted network planning solutions anetwork provider could deploy to improve customer experience and growtheir network share in an area. Furthermore, while existing planningsolutions may provide guidance on a high-level network improvementstrategy, they fail to provide insights that enable a network providerto take specific actions at lower area granularities, such as at a zipcode level. As a result, customers have to suffer through suboptimalcoverage and network providers have to expend considerable resources(e.g., engineering resources, monetary resources, etc.) before they cansee any positive results.

To solve these and other problems, the inventors have developed atelecommunications network planning system (“network planning system”)and method to identify a growth classification/categorization for thearea that helps a telecommunications network provider to solve for whattypes of planning opportunities are available for each location atvarious area granularities (e.g., sector, cell site, zip code, city,region, state, and so on). The network planning system computes valuesfor a set of growth criteria for a geographic area (e.g., sector, cellsite, city, zip code, state, region, etc.). The growth criteria arerelated to planning, area classification (e.g.,detractor/passive/promoter), customer experience, sales, population, andso on. Based on the growth-criteria values, the network planning systemidentifies a classification/categorization for the area. For example,the network planning system classifies an area as an invest area (e.g.,requiring engineering action), a grow area (e.g., requiring salesaction/being sales ready), a defend area (e.g., requiring engineeringand sales actions to continue current trend), or a fix area (e.g.,likely requiring both engineering and sales actions to improve currenttrend). Based on the area classification, the network planning systemcan then provide actionable insights to drive improvement in networkcoverage and customer experience. For example, the network planningsystem can recommend a network performance solution of spectrum additionto implement in the geographic area to improve network coverage and/orcongestion issues. The network planning system can also project changesin the growth criteria and area classification after the networkperformance solutions are deployed in the geographic area. This can helpthe network provider plan for and select solutions that will have themaximum impact on network performance and optimize network planninggoals. The network planning system provides a robust and extensivedashboard that enables telecommunications service providers to visualizethe various metrics generated by the network planning system, performwhat-if analysis, project the impact of deploying network performancesolutions at area locations, and so on.

In this manner, the network planning system provides an area-holisticsolution that enables a telecommunications network provider to identifylocations with suboptimum coverage, predict future coverage problems forcertain locations, and recommend solutions (e.g., adding a cell site,deploying a small cell, etc.) to optimize telecommunications networkcoverage in identified locations.

In the following description, for the purposes of explanation, numerousspecific details are set forth in order to provide a thoroughunderstanding of implementations of the present technology. It will beapparent, however, to one skilled in the art, that implementations ofthe present technology can be practiced without some of these specificdetails.

The phrases “in some implementations,” “according to someimplementations,” “in the implementations shown,” “in otherimplementations,” and the like generally mean the specific feature,structure, or characteristic following the phrase is included in atleast one implementation of the present technology and can be includedin more than one implementation. In addition, such phrases do notnecessarily refer to the same implementations or differentimplementations.

Wireless Communications System

FIG. 1 is a block diagram that illustrates a wireless telecommunicationnetwork 100 (“network 100”) in which aspects of the disclosed technologyare incorporated. The network 100 includes base stations 102-1 through102-4 (also referred to individually as “base station 102” orcollectively as “base stations 102”). A base station is a type ofnetwork access node (NAN) that can also be referred to as a cell site, abase transceiver station, or a radio base station. The network 100 caninclude any combination of NANs including an access point, radiotransceiver, gNodeB (gNB), NodeB, eNodeB (eNB), Home NodeB or HomeeNodeB, or the like. In addition to being a wireless wide area network(WWAN) base station, a NAN can be a wireless local area network (WLAN)access point, such as an IEEE 802.11 access point.

The NANs of a network 100 formed by the network 100 also includewireless devices 104-1 through 104-7 (referred to individually as“wireless device 104” or collectively as “wireless devices 104”) and acore network 106. The wireless devices 104-1 through 104-7 cancorrespond to or include network 100 entities capable of communicationusing various connectivity standards. For example, a 5G communicationchannel can use millimeter wave (mmW) access frequencies of 28 GHz ormore. In some implementations, the wireless device 104 can operativelycouple to a base station 102 over a long-term evolution/long-termevolution-advanced (LTE/LTE-A) communication channel, which is referredto as a 4G communication channel.

The core network 106 provides, manages, and controls security services,user authentication, access authorization, tracking, Internet Protocol(IP) connectivity, and other access, routing, or mobility functions. Thebase stations 102 interface with the core network 106 through a firstset of backhaul links (e.g., S1 interfaces) and can perform radioconfiguration and scheduling for communication with the wireless devices104 or can operate under the control of a base station controller (notshown). In some examples, the base stations 102 can communicate witheach other, either directly or indirectly (e.g., through the corenetwork 106), over a second set of backhaul links 110-1 through 110-3(e.g., X1 interfaces), which can be wired or wireless communicationlinks.

The base stations 102 can wirelessly communicate with the wirelessdevices 104 via one or more base station antennas. The cell sites canprovide communication coverage for geographic coverage areas 112-1through 112-4 (also referred to individually as “coverage area 112” orcollectively as “coverage areas 112”). The geographic coverage area 112fora base station 102 can be divided into sectors making up only aportion of the coverage area (not shown). The network 100 can includebase stations of different types (e.g., macro and/or small cell basestations). In some implementations, there can be overlapping geographiccoverage areas 112 for different service environments (e.g.,Internet-of-Things (IoT), mobile broadband (MBB), vehicle-to-everything(V2X), machine-to-machine (M2M), machine-to-everything (M2X),ultra-reliable low-latency communication (URLLC), machine-typecommunication (MTC), etc.).

The network 100 can include a 5G network 100 and/or an LTE/LTE-A orother network. In an LTE/LTE-A network, the term eNB is used to describethe base stations 102, and in 5G new radio (NR) networks, the term gNBsis used to describe the base stations 102 that can include mmWcommunications. The network 100 can thus form a heterogeneous network100 in which different types of base stations provide coverage forvarious geographic regions. For example, each base station 102 canprovide communication coverage for a macro cell, a small cell, and/orother types of cells. As used herein, the term “cell” can relate to abase station, a carrier or component carrier associated with the basestation, or a coverage area (e.g., sector) of a carrier or base station,depending on context.

A macro cell generally covers a relatively large geographic area (e.g.,several kilometers in radius) and can allow access by wireless devicesthat have service subscriptions with a wireless network 100 serviceprovider. As indicated earlier, a small cell is a lower-powered basestation, as compared to a macro cell, and can operate in the same ordifferent (e.g., licensed, unlicensed) frequency bands as macro cells.Examples of small cells include pico cells, femto cells, and microcells. In general, a pico cell can cover a relatively smaller geographicarea and can allow unrestricted access by wireless devices that haveservice subscriptions with the network 100 provider. A femto cell coversa relatively smaller geographic area (e.g., a home) and can providerestricted access by wireless devices having an association with thefemto unit (e.g., wireless devices in a closed subscriber group (CSG),wireless devices for users in the home). A base station can support oneor multiple (e.g., two, three, four, and the like) cells (e.g.,component carriers). All fixed transceivers noted herein that canprovide access to the network 100 are NANs, including small cells.

The communication networks that accommodate various disclosed examplescan be packet-based networks that operate according to a layeredprotocol stack. In the user plane, communications at the bearer orPacket Data Convergence Protocol (PDCP) layer can be IP-based. A RadioLink Control (RLC) layer then performs packet segmentation andreassembly to communicate over logical channels. A Medium Access Control(MAC) layer can perform priority handling and multiplexing of logicalchannels into transport channels. The MAC layer can also use Hybrid ARQ(HARQ) to provide retransmission at the MAC layer, to improve linkefficiency. In the control plane, the Radio Resource Control (RRC)protocol layer provides establishment, configuration, and maintenance ofan RRC connection between a wireless device 104 and the base stations102 or core network 106 supporting radio bearers for the user planedata. At the Physical (PHY) layer, the transport channels are mapped tophysical channels.

Wireless devices can be integrated with or embedded in other devices. Asillustrated, the wireless devices 104 are distributed throughout thenetwork 100, where each wireless device 104 can be stationary or mobile.For example, wireless devices can include handheld mobile devices 104-1and 104-2 (e.g., smartphones, portable hotspots, tablets, etc.); laptops104-3; wearables 104-4; drones 104-5; vehicles with wirelessconnectivity 104-6; head-mounted displays with wireless augmentedreality/virtual reality (AR/VR) connectivity 104-7; portable gamingconsoles; wireless routers, gateways, modems, and other fixed-wirelessaccess devices; wirelessly connected sensors that provide data to aremote server over a network; IoT devices such as wirelessly connectedsmart home appliances, etc.

A wireless device (e.g., wireless devices 104-1, 104-2, 104-3, 104-4,104-5, 104-6, and 104-7) can be referred to as a user equipment (UE), acustomer premise equipment (CPE), a mobile station, a subscriberstation, a mobile unit, a subscriber unit, a wireless unit, a remoteunit, a handheld mobile device, a remote device, a mobile subscriberstation, terminal equipment, an access terminal, a mobile terminal, awireless terminal, a remote terminal, a handset, a mobile client, aclient, or the like.

A wireless device can communicate with various types of base stationsand network 100 equipment at the edge of a network 100 including macroeNBs/gNBs, small cell eNBs/gNBs, relay base stations, and the like. Awireless device can also communicate with other wireless devices eitherwithin or outside the same coverage area of a base station viadevice-to-device (D2D) communications.

The communication links 114-1 through 114-9 (also referred toindividually as “communication link 114” or collectively as“communication links 114”) shown in network 100 include uplink (UL)transmissions from a wireless device 104 to a base station 102, and/ordownlink (DL) transmissions from a base station 102 to a wireless device104. The downlink transmissions can also be called forward linktransmissions while the uplink transmissions can also be called reverselink transmissions. Each communication link 114 includes one or morecarriers, where each carrier can be a signal composed of multiplesub-carriers (e.g., waveform signals of different frequencies) modulatedaccording to the various radio technologies. Each modulated signal canbe sent on a different sub-carrier and carry control information (e.g.,reference signals, control channels), overhead information, user data,etc. The communication links 114 can transmit bidirectionalcommunications using frequency division duplex (FDD) (e.g., using pairedspectrum resources) or time division duplex (TDD) operation (e.g., usingunpaired spectrum resources). In some implementations, the communicationlinks 114 include LTE and/or mmW communication links.

In some implementations of the network 100, the base stations 102 and/orthe wireless devices 104 include multiple antennas for employing antennadiversity schemes to improve communication quality and reliabilitybetween base stations 102 and wireless devices 104. Additionally oralternatively, the base stations 102 and/or the wireless devices 104 canemploy multiple-input, multiple-output (MIMO) techniques that can takeadvantage of multi-path environments to transmit multiple spatial layerscarrying the same or different coded data.

5G Core Network Functions

FIG. 2 is a block diagram that illustrates an architecture 200 including5G core network functions (NFs) that can implement aspects of thepresent technology. A wireless device 202 can access the 5G networkthrough a NAN (e.g., gNB) of a radio access network (RAN) 204. The NFsinclude an Authentication Server Function (AUSF) 206, a Unified DataManagement (UDM) 208, an Access and Mobility Management Function (AMF)210, a Policy Control Function (PCF) 212, a Session Management Function(SMF) 214, a User Plane Function (UPF) 216, and a Charging Function(CHF) 218.

The interfaces N1 through N15 define communications and/or protocolsbetween each NF as described in relevant standards. The UPF 216 is partof the user plane and the AMF 210, SMF 214, PCF 212, AUSF 206, and UDM208 are part of the control plane. One or more UPFs can connect with oneor more data networks (DNs) 220. The UPF 216 can be deployed separatelyfrom control plane functions. The NFs of the control plane aremodularized such that they can be scaled independently. As shown, eachNF service exposes its functionality in a Service Based Architecture(SBA) through a Service Based Interface (SBI) Message Bus 221 that usesHTTP/2. The SBA can include a Network Exposure Function (NEF) 222, an NFRepository Function (NRF) 224, a Network Slice Selection Function (NSSF)226, and other functions such as a Service Communication Proxy (SCP)(not shown).

The SBA can provide a complete service mesh with service discovery, loadbalancing, encryption, authentication, and authorization forinterservice communications. The SBA employs a centralized discoveryframework that leverages the NRF 224, which maintains a record ofavailable NF instances and supported services. The NRF 224 allows otherNF instances to subscribe and be notified of registrations from NFinstances of a given type. The NRF 224 supports service discovery byreceipt of discovery requests from NF instances and, in response,details which NF instances support specific services.

The NSSF 226 enables network slicing, which is a capability of 5G tobring a high degree of deployment flexibility and efficient resourceutilization when deploying diverse network services and applications. Alogical end-to-end (E2E) network slice has pre-determined capabilities,traffic characteristics, service-level agreements, and includes thevirtualized resources required to service the needs of a Mobile VirtualNetwork Operator (MVNO) or group of subscribers, including a dedicatedUPF, SMF, and PCF. The wireless device 202 is associated with one ormore network slices, which all use the same AMF. A Single Network SliceSelection Assistance Information (S-NSSAI) function operates to identifya network slice. Slice selection is triggered by the AMF, which receivesa wireless device registration request. In response, the AMF retrievespermitted network slices from the UDM 208 and then requests anappropriate network slice of the NSSF 226.

The UDM 208 introduces a User Data Convergence (UDC) that separates aUser Data Repository (UDR) for storing and managing subscriberinformation. As such, the UDM 208 can employ the UDC under 3GPP TS22.101 to support a layered architecture that separates user data fromapplication logic. The UDM 208 can include a stateful message store tohold information in local memory or can be stateless and storeinformation externally in a database of the UDR. The stored data caninclude profile data for subscribers and/or other data that can be usedfor authentication purposes. Given a large number of wireless devicesthat can connect to a 5G network, the UDM 208 can contain voluminousamounts of data that is accessed for authentication. Thus, the UDM 208is analogous to a Home Subscriber Server (HSS), providing authenticationcredentials while being employed by the AMF 210 and SMF 214 to retrievesubscriber data and context.

The PCF 212 can connect with one or more application functions (AFs)228. The PCF 212 supports a unified policy framework within the 5Ginfrastructure for governing network behavior. The PCF 212 accesses thesubscription information required to make policy decisions from the UDM208, and then provides the appropriate policy rules to the control planefunctions so that they can enforce them. The SCP provides a highlydistributed multi-access edge compute cloud environment and a singlepoint of entry for a cluster of network functions, once they have beensuccessfully discovered by the NRF 224. This allows the SCP to becomethe delegated discovery point in a datacenter, offloading the NRF 224from distributed service meshes that make up a network operator'sinfrastructure. Together with the NRF 224, the SCP forms thehierarchical 5G service mesh.

The AMF 210 receives requests and handles connection and mobilitymanagement while forwarding session management requirements over the N11interface to the SMF 214. The AMF 210 determines that the SMF 214 isbest suited to handle the connection request by querying the NRF 224.That interface and the N11 interface between the AMF 210 and the SMF 214assigned by the NRF 224 use the SBI 221. During session establishment ormodification, the SMF 214 also interacts with the PCF 212 over the N7interface and the subscriber profile information stored within the UDM208. Employing the SBI 221, the PCF 212 provides the foundation of thepolicy framework which, along with the more typical quality of serviceand charging rules, includes network slice selection, which is regulatedby the NSSF 226.

The Network Planning System

FIG. 3 is a block diagram that illustrates components of a networkplanning system 308. The network coverage optimization system 308 caninclude functional modules that are implemented with a combination ofsoftware (e.g., executable instructions or computer code) and hardware(e.g., at least a memory and processor). Accordingly, as used herein, insome examples a module is a processor-implemented module or set of code,and it represents a computing device having a processor that is at leasttemporarily configured and/or programmed by executable instructionsstored in memory to perform one or more of the specific functionsdescribed herein. For example, the network coverage optimization system308 can include a network monitoring and data collection module 310, atelecommunications network growth criteria selection module 330, atelecommunications network growth criteria scoring and weights module340, a geographic area classification module 350, an optimum solutionranking and selection module 360, and a reporting module 365, each ofwhich is discussed separately below.

Network Monitoring and Data Collection Module

The network monitoring and data collection module 310 is configuredand/or programmed to monitor telecommunications network data for ageographic area and extract, from that data, values of one or moregrowth criteria. The network monitoring and data collection module 310can monitor and extract the values of the growth criteria before aparticular network performance improvement solution is deployed(pre-solution deployment), after the particular network performanceimprovement solution is deployed (post-solution deployment), or both.

The network monitoring and data collection module 310collects/receives/accesses one or more of the following data recordsassociated with the growth, criteria (which can be stored in a networkplanning database 370): coverage records (e.g., number of covered usersin a geographic area, number of uncovered users in the geographic area,etc.), population of the geographic area, number of voice customers inthe geographic area, market share, usability of the geographic area,location specific records (LSRs), call data records (CDRs), timingadvance values, RF signal data, distance between the customer and atleast one telecommunications network site, strength of signal, quantityof data used, type of device of the customer, applications data (e.g.,application type, name, owner, manager, data sent/received/used/saved,bandwidth used, APIs accessed, etc.), source of usage records (forexample, telecommunications service provider, third party, applicationowner, etc.). The network monitoring and data collection module 310 cancollect/generate information about a usability index that reflects theusability of the geographic area as discussed in, for example,Applicants' co-pending patent application Ser. No. 17/554,595 titledTELECOMMUNICATIONS NETWORK COVERAGE OPTIMIZATION SYSTEM. Examples ofother types of data collected by the network monitoring and datacollection module 310 include, but are not limited to, data collectedfrom third-party applications (e.g., including crowdsourced data) thatcan help to determine customer experience with location. For example,the network monitoring and data collection module 310 can collectinformation about a user's location using his/her social media posts(e.g., tweets, check-ins, posts, etc.). As another example, the networkmonitoring and data collection module 310 collects application-leveldata (e.g., collected using applications related to IoT devices,sensors, billing meters, traffic lights, etc.) to identify the userlocation and/or data related to the performance indicators.

In some implementations, the network monitoring and data collectionmodule 310 monitors and/or collects data records corresponding toparticular time periods, such as morning, afternoon, evening, busyhours, and so on. The busy hour time period can vary for differentgeographic areas based on factors such as density of records, frequencyof user complaints, frequency of network coverage issues, and so on. Forexample, the busy hour time period can correspond to rush hour in ageographic area. In some implementations, the telecommunications networkdata for a geographic area is monitored at a cell level. The networkmonitoring and data collection module 310 can aggregate network data forvarious granularities, such as aggregating the cell-leveltelecommunications network data into sector-level and/or zip code-leveltelecommunications network data.

Telecommunications Network Growth Criteria Selection Module

The telecommunications network growth criteria selection module 330 isconfigured and/or programmed to select a set of growth criteria from aset of performance indicators (PIs). The set of PIs comprises hundreds(for example, 200-300) of performance indicators, each of which can beused to measure an aspect of performance of a specific geographic area(e.g., a cell site, sector, zip code, hex bin, region, state, country,and so on). For example, the set of PIs can include some or all of thefollowing performance indicators: sales metrics, planning metrics,network metrics, usability metrics, population metrics, customer metrics(e.g., number of customers, type of customers, etc.), network coveragemetrics, usability index, population, store locations, traffic, downlinkspeed, uplink speed, network measurement, types of handsets, accessfailures, geographic locations of sectors in the set of sectors, numberof sectors used, number of cell sites used, and so on.

From this set of numerous performance indicators, the telecommunicationsnetwork growth criteria selection module 330 selects a set of networkgrowth criteria to be used to evaluate network coverage and projectimpact/performance of various network performance improvement solutions.The telecommunications network growth criteria in the set oftelecommunications network growth criteria correspond to one or more ofthe following: network coverage, network planning metrics, networkusability, quality of service, data speed, and number of voicecustomers. The telecommunications network growth criteria selectionmodule 330 selects the subset of network growth criteria based on one ormore of the following factors: correlation of each network growthcriteria with customer experience, correlation of each network growthcriteria with other network growth criteria, user (for example,administrator) preference, telecommunications service providerpreference, and so on. For instance, the telecommunications networkgrowth criteria selection module 330 selects performance indicators thatexhibit a low degree of correlation yet reflect the dimensions of theoverall composite. For example, the telecommunications network growthcriteria selection module 330 selects the following network usabilityindicators as components of the set of network growth criteria: sales,planning, network, population, and store locations. Alternatively oradditionally, the telecommunications network growth criteria selectionmodule 330 selects a top threshold number of performance indicatorshaving a maximum correlation with the customer experience. In someimplementations, the telecommunications network growth criteriaselection module 330 selects the set of network growth criteria based onprincipal component analysis.

Telecommunications Network Growth Criteria Scoring and Weights Module

The telecommunications network growth criteria scoring and weightsmodule 340 is configured and/or programmed to compute scores and weightsfor the network growth criteria in the set of network growth criteria.The telecommunications network growth criteria scoring and weightsmodule 340 computes the weights that reflect the relative importance ofthe network growth criteria and/or minimize interdependence of networkgrowth criteria in the set of network growth criteria (for example, toavoid double counting). The telecommunications network growth criteriascoring and weights module 340 can compute the weights based onprincipal component analysis. In some implementations, thetelecommunications network growth criteria scoring and weights module340 can compute the weights based on one or more of the followingfactors: relative importance, number of potential customers available inthe geographic area, competition with other providers, customer churn,volume of customer complaints, and so on.

Additionally, the telecommunications network growth criteria scoring andweights module 340 computes score values for the network growth criteriain the set of network growth criteria. To compute the score values, thetelecommunications network growth criteria scoring and weights module340 can evaluate the values monitored and extracted by the networkmonitoring and data collection module 310. For example, to compute ascore value for the sales growth criterion, the telecommunicationsnetwork growth criteria scoring and weights module 340 first computes ageographic area penetration value (e.g., zip penetration value) asfollows:

${penetration}_{{geographic}{area}} = \frac{{number}{of}{customers}_{{geographic}{area}}}{{living}{population}_{{geographic}{area}}}$

For example, the penetration value for a zip code with 500 voicecustomers and a living population of 1000 is computed as 50%. Thepenetration value can then be compared with a market share value for thenetwork service provider to yield a score value for the sales growthcriterion. For example, when the zip penetration value is less than themarket share value, the score value for the sales growth criteria is 0.As another example, the telecommunications network growth criteriascoring and weights module 340 can compute a ratio of the zippenetration value and the market share value and then normalize theresult to yield a score value for the sales growth criterion between 0and 1 (or any other desired range).

Similarly, to compute a score value for the planning growth criterion,the telecommunications network growth criteria scoring and weightsmodule 340 first computes a geographic area in-building residentialcoverage (IBR) value that is indicative of the amount of coveredpopulation as follows:

${IBR}_{{geographic}{area}} = \frac{{number}{of}{covered}{population}_{{geographic}{area}}}{{living}{population}_{{geographic}{area}}}$

For example, the IBR value for a zip code with 4000 covered customersand a living population of 5000 is computed as 80%. The IBR value canthen be compared with a threshold value to yield a score value for thesales growth criterion. The threshold value can be based on churncorrelation (e.g., by correlating each threshold to churn and pickingthe threshold where churn started up ticking). For example, when the IBRvalue is less than the threshold value of 80%, the score value for theplanning growth criteria is 0. As another example, thetelecommunications network growth criteria scoring and weights module340 can compute a score value for the planning growth criterion based onthe IBR value and the number of uncovered population value.

The usability growth criterion value can be computed using the methodsdescribed in Applicants' co-pending patent application Ser. No.17/554,595 titled TELECOMMUNICATIONS NETWORK COVERAGE OPTIMIZATIONSYSTEM, the contents of which are incorporated herein in their entirety.The population growth criterion value can be computed by comparing thepopulation of the geographic area with a threshold value (e.g., 500).The network provider stores growth criterion value can be computed basedon a number of stores within a threshold radius distance from thegeographic area (for example, number of stores within 30 miles of a zipcode).

Geographic Area Classification Module

The geographic area classification module 350 is configured and/orprogrammed to determine a classification of the geographic area.Examples of classifications include, but are not limited to, thefollowing: invest, grow, defend, fix, and so on. The geographic areaclassifications can be determined by evaluating the score and/or weightvalues of one or more of the identified growth criteria. For example, asillustrated in FIG. 5 , the following growth criteria are used togenerate a classification 540, 545, 550, 555, or 560 for a zip code:sales 505, planning 510, network 515, population 520, and stores 525.

As illustrated in FIG. 5 , the zip code area is classified as an investarea 540 when the following criteria are met: sales: zip penetration isless than the market share value; planning: the. IBR value is less thana threshold value of 80% and the uncovered population is greater than athreshold value of 5000; network: the area is classified as a detractor,passive, or promoter area; and population: the total population isgreater than 500.

The geographic area classifications are used to select one or morenetwork performance improvement solutions/actions to deploy atparticular geographic areas/sites. For example, an invest classificationcan denote to the network planning system that telecommunicationsnetwork coverage in an identified geographic area can be optimized bydeploying both engineering and sales-related network improvementsolutions. As another example, a grow classification can denote to thenetwork planning system that while the network coverage quality iscurrently optimal, customer base in the identified geographic area canbe optimized by deploying sales-related solutions. FIG. 6 illustratessome example geographic area classifications 605, 610, 615, and 620, andassociated network improvement opportunities/solutions. An area can beclassified as Fix 1 when it has good, predicted coverage but poorcustomer experience from mobile measure data. Similarly, an area can beclassified as Fix 2 when it has poor predicted coverage with lowuncovered pops.

Optimum Solution Ranking and Selection Module

The optimum solution ranking and selection module 360 of FIG. 3 isconfigured and/or programmed to enable selection of one (or more)network performance improvement solutions/actions to deploy atparticular geographic areas/sites. Examples of network performanceimprovement solutions include, but are not limited to, cell split, smallcell deployment, spectrum addition, spectrum removal, sector addition,sector removal, and so on. The optimum solution ranking and selectionmodule 360 evaluates the classifications generated for a geographic areato identify and select one or more solutions as candidates fordeployment in that area (for example, at a cell site associated with thearea). The optimum solution ranking and selection module 360 can computethe impact of deploying a solution on individual network growth criteriavalues/scores and/or the overall telecommunications networkclassification for the geographic area. Growth can be determined basedon current market share. For example, assuming a provider has 20% marketshare in 1000 populated area, the growth is computed to be(40−20)*1000=200 potential lines (40 being the target market share). Insome implementations, the optimum solution ranking and selection module360 evaluates the impact of short-term solutions, medium-term solutions,and long-term solutions to identify an optimum set of solutions toselect for the geographic area. The solutions can be ranked in the orderof decreasing impact on area classification. In some implementations,the optimum solution ranking and selection module 360 selects thebest-performing solution (for example, small cell). The followinginformation can also be stored/displayed about the network performanceimprovement solutions: solutions count (total number of sites/sectorswhere the solution is deployed) and percentage of sites/sectors where aclassification change occurred.

FIG. 7 illustrates the impact of deploying various performanceimprovement solutions/actions on the classifications for variousgeographic areas in a region (western United States) over a period oftime (current 705, End of Year 2022 710, and End of Year 2023 715). Asillustrated in FIG. 7 , the network planning system enables a user tovisualize the current and future area classifications in a map format705 a, 710 a, and 715 a, and/or a table format 705 b, 710 b, and 715 b.For example, FIG. 7 (705 a, 705 b) illustrates zip areas where a serviceprovider can invest in and fix from engineering side versus grow anddefend areas for sales-type network performance improvementsolutions/actions. Based on the plan of records of network investmentsfor a service provider, the system can predict customer experience andcoverage. The system can combine these (and/or other predictions) togenerate a predicted value of the growth categories/classifications. Forexample, an area with a current IBR of 70% IBR and a current usabilityindex value of 70 would be currently classified as an invest area. Thesystem determines that after deploying the identified networkperformance improvement solutions/actions, the IBR is expected toimprove to 90% and the usability index is expected to change to 80. As aresult, the area classification will change to a Grow area by EOY 2022.FIG. 7 (710 a, 710 b, 715 a, 715 b) illustrates predicted market sharebased upon the potential lines from grow and defend area. Assuming theservice provider has 10% market share, 1000 customers, 10000 currentcovered population and 2000 potential population to be covered, thesystem can generate a forecast of current to potential customers (growand defend areas) which will be (1000+2000)/10000=30% market sharepotential gain.

Table 705 b illustrates the following information about the areaclassifications/categories (invest, grow, defend, fix, and lowpopulation): number of zip codes with that classification, number ofimpacted residents (#of population), and percentage of population (% ofpopulation).

In addition to evaluating the impact on geographic classification ofvarious solutions, the optimum solution ranking and selection module 360can consider one or more of the following additional factors whenranking and/or selecting optimum solutions: location of thetelecommunications network site, lease information of thetelecommunications network site, duration of deployment of the networkperformance improvement solution, entitlements and permits required todeploy the network performance improvement solution, tower height,nearest available site, population served by the telecommunicationsnetwork site, households served by the telecommunications network site,rental costs associated with the network performance improvementsolution, backhaul availability, cost and duration factors (e.g., costof deploying a network performance improvement solution, cost ofmaintaining the network performance improvement solution, expectedlifetime of the network performance improvement solution, duration ofdeploying the network performance improvement solution, lifetime of thenetwork performance improvement solution), similarity between the sitewhere a solution was deployed and the site where the solution is to bedeployed, solutions deployed at sites in a selected geographic area, andso on. For example, while the optimum solution ranking and selectionmodule 360 initially selects a small cell solution as an optimumsolution based on the impact on geographic classification, it can updateits selection to a sector addition solution based on the costs andduration of deployment associated with the various solutions (small cellsolutions tend to be more expensive and take a longer time to deploy, ascompared to, sector addition solutions).

Reporting Module

The reporting module 365 of FIG. 3 is configured and/or programmed togenerate one or more reports that can be displayed at a user interface.FIGS. 8A-8D are example reports illustrating analysis of data relatingto network planning in a telecommunications network. FIG. 8A illustratesa report 805 that displays the classifications/categories for an area(for example, zip code categories for the state of California on a map805 a), as well as details within each category 805 c. An area can beclassified as “needs distribution” by executing a spatial query througha centroid of the area. When the area is classified as a “grow” area andhas no service provider store within a threshold distance (e.g., 30miles of the radius), the area is classified as “needs distribution.”Section 805 c shows potential customers a service provider can gain fromeach zip code category. In addition, report 805 displays the potentialfor additional growth and the potential lines 805 b. A service providercan utilize the information to improve coverage issues. Report 805 canfurther display one or more metrics comparing the service provider withits competitors 805 d, enabling the service provider to identifycompetitors to whim they are losing market share, competitors from whomthey are gaining market share, and so on.

Section 805 e illustrates on-air network towers and plan investments.Some are new builds (brand new location) and some are modifications.Their total sum is roughly equivalent to around 2B dollars. This giveinsights of how much a service provider has and how much it can plan toadd in the future.

FIG. 8B illustrates a report 810 that displays a current view and aprojected view for a geographic area. For example, report 810 candisplay a section 810 a illustrating various metrics associated with ageographic area (e.g., total population, number of customers, potentiallines, usability index, IBR coverage %, and market penetration). Inaddition, report 810 can display a map (810 b) plotting the zip codesand their associated categories. Report 810 can further display thecurrent growth categorization 810 c of the geographic area and theprojected growth categorization 810 d of the geographic area. Theinformation illustrated in report 810 can be used to determine how muchtotal population, potential lines, customers a service provider has ineach category of zip code. It enables drill down on any particularcounty, MSA, City. This drill down enables a service provider to viewcurrent state information as well as future state information (e.g., byselecting filters on right to select various years, such as 2022, 2023and so on). This is very powerful because it enables a sales team toidentify when an area will be ready for certain performance improvementsolutions/actions, and enables an for engineering team to plan thesolutions if an area is invest even after 2020 build plan.

FIGS. 8C and 8D illustrate reports 815 and 820, respectively, whichdisplay various, geographic areas and their associated rankings.«Question for inventors—as before, can you add more explanation aboutwhat this screen is displaying? How can the controls on the right beused to alter the info displayed on the left? How is this info used bysales and networking teams to make intelligent decisions?>> Reports 815and 820 enable a service provider to identify priority areas. Forexample, using the example reports illustrated in FIGS. 8C and 8D, aservice provider can identify Sacramento as having #1 market forpotential growth. Once Sacramento is selected, a user can identify lowergranularity areas within the selected area (e.g., Sacramento) fornetwork planning purposes.

Flow Diagrams

FIG. 4 is a flow diagram illustrating a process of optimizing coveragein a telecommunications network. At block 405, process 400 monitorstelecommunications network data (e.g., for a geographic area). At block410, process 400 evaluates telecommunications coverage data for one ormore geographic areas. For example, process 400 examines thetelecommunications coverage data for a geographic area and selects a setof network growth criteria to be used to evaluate network coverage andproject impact/performance of various network performance improvementsolutions. The telecommunications network growth criteria in the set oftelecommunications network growth criteria correspond to one or more ofthe following: network coverage, network planning metrics, networkusability, quality of service, data speed, and number of voicecustomers.

At block 415, process 400 computes values of each telecommunicationsnetwork growth criterion in the set of telecommunications network growthcriteria. At block 420, process 400 generates a weight for eachtelecommunications network growth criterion in the set oftelecommunications network growth criteria. Using the values and theweights of the telecommunications network growth criteria in the set oftelecommunications network growth criteria, at block 425, process 400computes a classification/categorization for the geographic area(s). Atblock 430, process 400 uses the computed classification/categorizationto identify whether one or more of the geographic areas have any networkcoverage/planning issues. At block 435, process 400 can use the computedclassification/categorization for the geographic area(s) to provide datafor selecting an optimum network performance improvement solution to beimplemented at the geographic area to improve coverage issues.

Computer System

FIG. 9 is a block diagram that illustrates an example of a computersystem 900 in which at least some operations described herein can beimplemented. As shown, the computer system 900 can include one or moreprocessors 902, main memory 906, non-volatile memory 910, a networkinterface device 912, a display device 918, an input/output device 920,a control device 922 (e.g., a keyboard and pointing device), a driveunit 924 that includes a machine-readable (storage) medium 926, and asignal generation device 930, all of which are communicatively connectedto a bus 916. The bus 916 represents one or more physical buses and/orpoint-to-point connections that are connected by appropriate bridges,adapters, or controllers. Various common components (e.g., cache memory)are omitted from FIG. 9 for brevity. Instead, the computer system 900 isintended to illustrate a hardware device on which components illustratedor described relative to the examples of the figures and any othercomponents described in this specification can be implemented.

The computer system 900 can take any suitable physical form. Forexample, the computer system 900 can have an architecture similar tothat of a server computer, personal computer (PC), tablet computer,mobile telephone, game console, music player, wearable electronicdevice, network-connected (“smart”) device (e.g., a television or homeassistant device), AR/VR system (e.g., head-mounted display), or anyelectronic device capable of executing a set of instructions thatspecify action(s) to be taken by the computer system 900. In someimplementations, the computer system 900 can be an embedded computersystem, a system-on-chip (SOC), a single-board computer system (SBC), ora distributed system such as a mesh of computer systems, or it mayinclude one or more cloud components in one or more networks. Whereappropriate, one or more computer systems 900 can perform operations inreal time, in near real time, or in batch mode.

The network interface device 912 enables the computer system 900 tomediate data in a network 914 with an entity that is external to thecomputer system 900 through any communication protocol supported by thecomputer system 900 and the external entity. Examples of the networkinterface device 912 include a network adaptor card, a wireless networkinterface card, a router, an access point, a wireless router, a switch,a multilayer switch, a protocol converter, a gateway, a bridge, a bridgerouter, a hub, a digital media receiver, and/or a repeater, as well asall wireless elements noted herein.

The memory (e.g., main memory 906, non-volatile memory 910, andmachine-readable (storage) medium 926) can be local, remote, ordistributed. Although shown as a single medium, the machine-readable(storage) medium 926 can include multiple media (e.g., acentralized/distributed database and/or associated caches and servers)that store one or more sets of instructions 928. The machine-readable(storage) medium 926 can include any medium that is capable of storing,encoding, or carrying a set of instructions for execution by thecomputer system 900. The machine-readable (storage) medium 926 can benon-transitory or comprise a non-transitory device. In this context, anon-transitory storage medium can include a device that is tangible,meaning that the device has a concrete physical form, although thedevice can change its physical state. Thus, for example, non-transitoryrefers to a device remaining tangible despite this change in state.

Although implementations have been described in the context of fullyfunctioning computing devices, the various examples are capable of beingdistributed as a program product in a variety of forms. Examples ofmachine-readable storage media, machine-readable media, orcomputer-readable media include recordable-type media such as volatileand non-volatile memory devices, removable flash memory, hard diskdrives, optical disks, and transmission-type media such as digital andanalog communication links.

In general, the routines executed to implement examples herein can beimplemented as part of an operating system or a specific application,component, program, object, module, or sequence of instructions(collectively referred to as “computer programs”). The computer programstypically comprise one or more instructions (e.g., instructions 904,908, 928) set at various times in various memory and storage devices incomputing device(s). When read and executed by the processor 902, theinstruction(s) cause the computer system 900 to perform operations toexecute elements involving the various aspects of the disclosure.

Remarks

The terms “example,” “embodiment,” and “implementation” are usedinterchangeably. For example, references to “one example” or “anexample” in the disclosure can be, but not necessarily are, referencesto the same implementation; and such references mean at least one of theimplementations. The appearances of the phrase “in one example” are notnecessarily all referring to the same example, nor are separate oralternative examples mutually exclusive of other examples. A feature,structure, or characteristic described in connection with an example canbe included in another example of the disclosure. Moreover, variousfeatures are described which can be exhibited by some examples and notby others. Similarly, various requirements are described which can berequirements for some examples but no other examples.

The terminology used herein should be interpreted in its broadestreasonable manner, even though it is being used in conjunction withcertain specific examples of the invention. The terms used in thedisclosure generally have their ordinary meanings in the relevanttechnical art, within the context of the disclosure, and in the specificcontext where each term is used. A recital of alternative language orsynonyms does not exclude the use of other synonyms. Specialsignificance should not be placed upon whether or not a term iselaborated or discussed herein. The use of highlighting has no influenceon the scope and meaning of a term. Further, it will be appreciated thatthe same thing can be said in more than one way.

Unless the context clearly requires otherwise, throughout thedescription and the claims, the words “comprise,” “comprising,” and thelike are to be construed in an inclusive sense, as opposed to anexclusive or exhaustive sense—that is to say, in the sense of“including, but not limited to.” As used herein, the terms “connected,”“coupled,” or any variant thereof means any connection or coupling,either direct or indirect, between two or more elements; the coupling orconnection between the elements can be physical, logical, or acombination thereof. Additionally, the words “herein,” “above,” “below,”and words of similar import can refer to this application as a whole andnot to any particular portions of this application. Where contextpermits, words in the above Detailed Description using the singular orplural number may also include the plural or singular number,respectively. The word “or” in reference to a list of two or more itemscovers all of the following interpretations of the word: any of theitems in the list, all of the items in the list, and any combination ofthe items in the list. The term “module” refers broadly to softwarecomponents, firmware components, and/or hardware components.

The above detailed description of implementations of the system is notintended to be exhaustive or to limit the system to the precise formdisclosed above. While specific implementations of, and examples for,the system are described above for illustrative purposes, variousequivalent modifications are possible within the scope of the system, asthose skilled in the relevant art will recognize. For example, somenetwork elements are described herein as performing certain functions.Those functions could be performed by other elements in the same ordiffering networks, which could reduce the number of network elements.Alternatively, or additionally, network elements performing thosefunctions could be replaced by two or more elements to perform portionsof those functions. In addition, while processes, message/data flows, orblocks are presented in a given order, alternative implementations canperform routines having blocks, or employ systems having blocks, in adifferent order, and some processes or blocks can be deleted, moved,added, subdivided, combined, and/or modified to provide alternatives orsubcombinations. Each of these processes, message/data flows, or blockscan be implemented in a variety of different ways. Also, while processesor blocks are at times shown as being performed in series, theseprocesses or blocks can instead be performed in parallel or can beperformed at different times. Further, any specific numbers noted hereinare only examples: alternative implementations can employ differingvalues or ranges.

Details of the disclosed implementations can vary considerably inspecific implementations while still being encompassed by the disclosedteachings. As noted above, particular terminology used when describingfeatures or aspects of the invention should not be taken to imply thatthe terminology is being redefined herein to be restricted to anyspecific characteristics, features, or aspects of the invention withwhich that terminology is associated. In general, the terms used in thefollowing claims should not be construed to limit the invention to thespecific examples disclosed herein, unless the above DetailedDescription explicitly defines such terms. Accordingly, the actual scopeof the invention encompasses not only the disclosed examples, but alsoall equivalent ways of practicing or implementing the invention underthe claims. Some alternative implementations can include additionalelements to those implementations described above or include fewerelements. The teachings of the methods and system provided herein can beapplied to other systems, not necessarily the system described above.The elements, blocks, and acts of the various implementations describedabove can be combined to provide further implementations.

Any patents and applications and other references noted above, and anythat may be listed in accompanying filing papers, are incorporatedherein by reference in their entireties, except for any subject matterdisclaimers or disavowals, and except to the extent that theincorporated material is inconsistent with the express disclosureherein, in which case the language in this disclosure controls. Aspectsof the invention can be modified to employ the systems, functions, andconcepts of the various references described above to provide yetfurther implementations of the invention.

To reduce the number of claims, certain implementations are presentedbelow in certain claim forms, but the applicants contemplate variousaspects of an invention in other forms. For example, aspects of a claimcan be recited in a means-plus-function form or in other forms, such asbeing embodied in a computer-readable medium. A claim intended to beinterpreted as a means-plus-function claim will use the words “meansfor.” However, the use of the term “for” in any other context is notintended to invoke a similar interpretation. The applicants reserve theright to pursue such additional claim forms either in this applicationor in a continuing application.

These and other changes can be made to the invention in light of theabove Detailed Description. While the above description describescertain implementations of the technology and describes the best modecontemplated, no matter how detailed the above appears in text, theinvention can be practiced in many ways. Details of the system can varyconsiderably in their implementation while still being encompassed bythe technology disclosed herein. As noted above, particular terminologyused when describing certain features or aspects of the technologyshould not be taken to imply that the terminology is being redefinedherein to be restricted to any specific characteristics, features, oraspects of the technology with which that terminology is associated. Ingeneral, the terms used in the following claims should not be construedto limit the invention to the specific implementations disclosed in thespecification, unless the above Detailed Description section explicitlydefines such terms. Accordingly, the actual scope of the inventionencompasses not only the disclosed implementations, but also allequivalent ways of practicing or implementing the invention under theclaims.

The invention claimed is:
 1. A system for identifying geographic areasin which to improve telecommunications network congestion, the systemcomprising: at least one hardware processor; at least one non-transitorymemory, coupled to the at least one hardware processor and storinginstructions, which, when executed by the at least one hardwareprocessor, perform a process, the process comprising: monitoringtelecommunications network data for a geographic area; evaluatingtelecommunications coverage data for the geographic area; computing,from the telecommunications network data and the telecommunicationscoverage data, values of growth criteria in a set of telecommunicationsgrowth criteria for the geographic area, wherein the growth criteria inthe set of telecommunications growth criteria correspond to at least twoof the following: telecommunications network planning,telecommunications network usability, or telecommunications networkcoverage; generating a weight for each growth criteria in the set oftelecommunications growth criteria; generating a classification of thegeographic area using the computed values and weights of the growthcriteria, wherein the geographic area is classified as an invest area, agrow area, a defend area, or a fix area; and using the generatedclassification of the geographic area to provide data for selecting anoptimum network performance improvement solution from a set of networkperformance improvement solutions to be implemented in at least onenetwork site or node in the geographic area.
 2. The system of claim 1,wherein the process monitors the telecommunications network data for thegeographic area during one or more busy hours.
 3. The system of claim 1,wherein the set of telecommunications growth criteria comprises: zippenetration, number of customers in the geographic area, number ofcustomer lines in the geographic area, population of the geographicarea, market share, network coverage, in-building residential coverage(IBR), network classification of the geographic area, number of serviceprovider locations in the geographic area, or any combination thereof.4. The system of claim 3, wherein the network classification of thegeographic area is one of: a detractor area, a passive area, or apromoter area.
 5. The system of claim 1, wherein the weights for growthcriteria are computed using principal component analysis.
 6. The systemof claim 1, wherein the weights for growth criteria are computed tominimize interdependence of growth criteria in the set of growthcriteria.
 7. The system of claim 1, wherein the telecommunicationsnetwork data for a geographic area is monitored at a cell level, andwherein the process further comprises aggregating the cell-leveltelecommunications network data into sector-level telecommunicationsnetwork data.
 8. The system of claim 1, wherein the set of networkperformance improvement solutions comprises: cell split, small celldeployment, spectrum addition, spectrum removal, sector addition, sectorremoval, or any combination thereof.
 9. The system of claim 1, whereinthe set of growth criteria comprises a top threshold number of growthcriteria having a maximum correlation with customer experience.
 10. Thesystem of claim 1, wherein the set of growth criteria comprises growthcriteria having low degrees of correlation with each other.
 11. Thesystem of claim 1, wherein the instructions, when executed by the atleast one hardware processor, further perform a process comprising: foreach growth criterion, projecting a change in value of the growthcriterion if a network performance improvement solution were to beimplemented in at least one network site or node in the geographic area,wherein the optimum network performance improvement solution isprojected to provide a maximum positive change in values of a majorityof the growth criteria.
 12. The system of claim 1, wherein theinstructions, when executed by the at least one hardware processor,further perform a process comprising: for each growth criterion,projecting a change in a number of users with a better experience if anetwork performance improvement solution were to be implemented in atleast one network site or node in the geographic area, wherein theoptimum network performance improvement solution is projected to providea maximum positive change in values of a majority of the growthcriteria.
 13. The system of claim 1, wherein the geographic area is asector, a cell site, a zip code, a city, a region, or a state.
 14. Acomputer-implemented method for identifying geographic areas in which toimprove telecommunications network congestion, the method comprising:monitoring telecommunications network data for a geographic area;evaluating telecommunications coverage data for the geographic area;computing, from the telecommunications network data and thetelecommunications coverage data, values of growth criteria in a set oftelecommunications growth criteria for the geographic area, wherein thegrowth criteria in the set of telecommunications growth criteriacorrespond to at least two of the following: telecommunications networkplanning, telecommunications network usability, or telecommunicationsnetwork coverage; generating a weight for each growth criteria in theset of telecommunications growth criteria; generating a classificationof the geographic area using the computed values and weights of thegrowth criteria, wherein the geographic area is classified as an investarea, a grow area, a defend area, or a fix area; and using the generatedclassification of the geographic area to provide data for selecting anoptimum network performance improvement solution from a set of networkperformance improvement solutions to be implemented in at least onenetwork site or node in the geographic area.
 15. The method of claim 14,wherein the set of telecommunications growth criteria comprises: zippenetration, number of customers in the geographic area, number ofcustomer lines in the geographic area, population of the geographicarea, market share, network coverage, in-building residential coverage(IBR), network classification of the geographic area, number of serviceprovider locations in the geographic area, or any combination thereof.16. The method of claim 14, wherein the set of network performanceimprovement solutions comprises: cell split, small cell deployment,spectrum addition, spectrum removal, sector addition, sector removal, orany combination thereof.
 17. The method of claim 14, further comprising:for each growth criterion, projecting a change in: (1) value of thegrowth criterion, or (2) a number of users with a better experience, or(3) both, if a network performance improvement solution were to beimplemented in at least one network site or node in the geographic area,wherein the optimum network performance improvement solution isprojected to provide a maximum positive change in values of a majorityof the growth criteria.
 18. At least one non-transitory,computer-readable storage medium carrying instructions, which, whenexecuted by at least one data processor, perform operations foridentifying geographic areas in which to improve telecommunicationsnetwork congestion, the operations comprising: receiving, at a graphicaluser interface, a selection of a geographic area; determining a set ofsub-areas within the selected geographic area; for each sub-area in theset of sub-areas within the selected geographic area: evaluating, forthe sub-area, a current classification of the sub-area as being aninvest area, a grow area, a defend area, or a fix area, wherein at leasttwo sub-areas in the set of sub-areas within the selected geographicarea have a different classification; determining a set of networkperformance improvement solutions to be implemented in at least onenetwork site or node in the sub-area; evaluating, for the sub-area, aprojected classification of the sub-area as being an invest area, a growarea, a defend area, or a fix area if one or more of the set of networkperformance improvement solutions were implemented in at least onenetwork site or node in the sub-area; and displaying, at the graphicaluser interface, the current classification of the sub-area and theprojected classification of the sub-area.
 19. The at least onenon-transitory, computer-readable storage medium of claim 18, whereinthe operations further comprise: displaying, at the graphical userinterface, an interactive map of the geographic area, wherein theinteractive map further displays indicators depicting sub-areas withinthe geographic area and the associated current classifications of thesub-areas.
 20. The at least one non-transitory, computer-readablestorage medium of claim 18, wherein the operations further comprise:displaying, at the graphical user interface, an interactive map of thegeographic area, wherein the interactive map further displays indicatorsdepicting sub-areas within the geographic area and the associatedcurrent classifications of the sub-areas; and in response to a userselection of a projected view, displaying the projected classificationsof the sub-areas.